Text analysis

GlotLID

Detects which language a text is written in: the third version covers more than two thousand labels, including Tatar, Bashkir, Chuvash, Udmurt, Mari, Erzya, Komi and other languages of Russia.

The last open version came out in Apr 2024. The family has not been updated for a long time: the model still works, but do not expect fixes or new sizes.

Developer
CIS, LMU Munich, Germany
First release
Oct 2023
Latest release
Apr 2024
Sizes
a FastText model; parameter count is not stated on the model card
License
Commercial use allowedApache 2.0 with additional notices (LICENSE file in the repository)
Russian
Supported
Running
On your own serverAlso runs without a GPU
Industries
Documents and accounting, Media and production, Science and research, Customer support
Deploy on your server Hugging Face GitHub

What it does

  • Sorting mixed text archives by language
  • Filtering out noise and foreign languages before training
  • Routing requests to the right operator or model
  • Checking the labelling of language corpora

Where it is used

Media and publishingResearch and language projectsCustomer support

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
fits
1 GPUOne GPU with 16–80 GB — mid-size versions
no versions
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. GlotLID v3, более двух тысяч меток языков
  2. GlotLID v1

How to run it

On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.Hugging Face
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems.

Frequently asked questions

Can GlotLID be used in a commercial project?

Yes. License: Apache 2.0 with additional notices (LICENSE file in the repository). It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does GlotLID need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does GlotLID support Russian?

Yes, Russian is listed on the model card.

Where can I download GlotLID and what does it cost?

The GlotLID weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

Similar models

Text analysismmBERTJohns Hopkins University (JHU CLSP) · USACommercial use allowed

A multilingual encoder trained on more than 1800 languages. The list includes Tatar, Bashkir, Chuvash, Udmurt, Buryat, Komi, Ingush and other languages of Russia. A base for classifiers and search over such texts.

DetailsText analysisXLM-RoBERTaMeta · USACommercial use allowed

A classic multilingual encoder for 100 languages, including Russian. The base of many sentiment, NER and embedding models, including BGE-M3.

DetailsSearch and RAGBGE-M3BAAI · ChinaCommercial use allowed

A model for meaning-based search in about a hundred languages. The core of RAG: the bot finds the right part of a document before answering.

Details

Source: huggingface.co/cis-lmu/glotlid. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.